1 The global distribution of reveals a need for targeted

2 conservation


4 Uri Roll#1,2, Anat Feldman#3, Maria Novosolov#3, Allen Allison4, Aaron M. Bauer5, Rodolphe

5 Bernard6, Monika Böhm7, Fernando Castro-Herrera8, Laurent Chirio9, Ben Collen10, Guarino R.

6 Colli11, Lital Dabool12 Indraneil Das13, Tiffany M. Doan14, Lee L. Grismer15, Marinus

7 Hoogmoed16, Yuval Itescu3, Fred Kraus17, Matthew LeBreton18, Amir Lewin3, Marcio Martins19,

8 Erez Maza3, Danny Meirte20, Zoltán T. Nagy21, Cristiano de C. Nogueira19, Olivier S.G.

9 Pauwels22, Daniel Pincheira-Donoso23, Gary Powney24, Roberto Sindaco25, Oliver Tallowin3,

10 Omar Torres-Carvajal26, Jean-François Trape27, Enav Vidan3, Peter Uetz28, Philipp Wagner5,29,

11 Yuezhao Wang30, C David L Orme6, Richard Grenyer✝1 and Shai Meiri✝*3


13 # Contributed equally to the paper

14 ✝ Contributed equally to the paper

15 * Corresponding author


17 Affiliations:

18 1 School of Geography and the Environment, University of Oxford, Oxford, OX13QY, UK.

19 2 Mitrani Department of Ecology, The Jacob Blaustein Institutes for Desert Research, 20 Ben-Gurion University, Midreshet Ben-Gurion 8499000, Israel. (Current address)

21 3 Department of , Tel-Aviv University, Tel-Aviv 6997801, Israel. 22 4 Hawaii Biological Survey, 4 Bishop Museum, Honolulu, HI 96817, USA.

23 5 Department of , Villanova University, Villanova, PA 19085, USA.

24 6 Department of Life Sciences, Imperial College London, Silwood Park Campus Silwood Park, 25 Ascot, Berkshire, SL5 7PY, UK

26 7 Institute of Zoology, Zoological Society of London, London NW1 4RY, UK.

27 8 School of Basic Sciences, Physiology Sciences Department, Universidad del Valle, Colombia.

28 9 14, rue des roses - 06130 Grasse, France.

29 10 Centre for & Environment Research, University College London, London WC1E 30 6BT, UK.

31 11 Departamento de Zoologia, Universidade de Brasília, 70910-900, Brasília, Distrito Federal, 32 Brazil.

33 12 Department of Genetics and Developmental Biology, The Rappaport Family Institute for 34 Research in the Medical Sciences, Faculty of Medicine, Technion – Israel Institute of 35 Technology, Haifa 31096, Israel.

36 13 Institute of Biodiversity and Environmental Conservation, Universiti Malaysia Sarawak, 37 94300 Kota Samarahan, Sarawak, Malaysia.

38 14 Department of Biology, University of Central Florida, Orlando, FL 32816, USA.

39 15 Department of Biology, La Sierra University, Riverside, CA 92505, USA.

40 16 Museu Paraense Emílio Goeldi/CZO, Caixa Postal 399, 66017–970 Belém, Pará, Brazil.

41 17 Department of Ecology and Evolutionary Biology, University of Michigan, Ann-Arbor, MI 42 48109-1048, USA.

43 18 Mosaic, (Environment, Health, Data, Technology), Yaoundé, Cameroon.

44 19 Departamento de Ecologia, Instituto de Biociências, Universidade de São Paulo, 05508-090 45 São Paulo, São Paulo, Brasil.

46 20 Royal Museum for Central Africa, Leuvensesteenweg 13, 3080 Tervuren, Belgium.

47 21 Joint Experimental Molecular Unit, Royal Belgian Institute of Natural Sciences, B-1000 48 Brussels, Belgium.

49 22 Département des Vertébrés Récents, Royal Belgian Institute of Natural Sciences, B-1000 50 Brussels, Belgium.

51 23 School of Life Sciences, Joseph Banks Laboratories, University of Lincoln, Brayford Campus, 52 Lincoln, LN6 7DL, UK. 53 24 NERC Centre for Ecology and Hydrology, Maclean Building, Crowmarsh Gifford, 54 Wallingford, OX10 8BB, UK.

55 25 Museo Civico di Storia Naturale, I-10022 Carmagnola (TO), Italy.

56 26 Museo de Zoología, Escuela de Ciencias Biológicas, Pontificia Universidad Católica del 57 Ecuador, Apartado 17-01-2184, Quito, Ecuador.

58 27 Institut de Recherche pour le Développement, Laboratoire de Paludologie et Zoologie 59 Médicale, UMR MIVEGEC, Dakar, Senegal.

60 28 Center for the Study of Biological Complexity, Virginia Commonwealth University, 61 Richmond, VA 23284, USA.

62 29 Zoologische Staatssammlung München, D-81247 München, Germany.

63 30 Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, China. 64 Abstract

65 The distributions of , and have underpinned global and local

66 conservation priorities, and have been fundamental to our understanding of the determinants of

67 . In contrast, the global distributions of , representing a third of

68 terrestrial diversity, have been unavailable. This prevented reptiles’ incorporation into

69 conservation planning and biased our understanding of the underlying processes governing

70 global vertebrate biodiversity. Here, we present and analyse, for the first time, the global

71 distribution of 10,064 reptile (99% of extant terrestrial species). We show that richness

72 patterns of the other three classes are good spatial surrogates for species richness of all

73 reptiles combined and of , but characterize diversity patterns of and poorly.

74 Hotspots of total and endemic richness overlap very little with those of other taxa.

75 Moreover, existing protected areas, sites of biodiversity significance and global conservation

76 schemes, represent birds and mammals better than reptiles. We show that additional conservation

77 actions are needed to effectively protect reptiles, particularly lizards and turtles. Adding reptile

78 knowledge to a global complementarity conservation priority scheme, identifies many locations

79 that consequently become important. Notably, investing resources in some of the world’s arid,

80 grassland, and savannah habitats might be necessary to represent all terrestrial

81 efficiently. 82 Introduction

83 Our knowledge of the distributions of a broad variety of organisms has improved greatly in the

84 past decade1-3. This has greatly aided our efforts to conserve biodiversity4-6 and significantly

85 enhanced our grasp of broad evolutionary and ecological processes7-12. Nevertheless,

86 despite comprising one third of terrestrial vertebrate species, knowledge of reptile distributions

87 remained poor and unsystematic. This represented a major gap in our understanding of the global

88 structure of biodiversity and our ability to conserve . Historically, broad-scale efforts

89 towards the protection of land vertebrates (and thus also of reptiles) have been based

90 predominantly on data from plants, birds, mammals and to a lesser degree amphibians13-15. Here

91 we present complete species-level global distributions of nearly all reptiles: 10,064 known,

92 extant, terrestrial species for which we could identify precise distribution information. These

93 distributions cover the (lizards, 6110 species), Serpentes (snakes, 3414 species),

94 Testudines (turtles, 322 species), (‘worm lizards’, 193 species), Crocodylia

95 (, 24 species) and (the , one species).

96 This dataset completes the global distribution mapping of all described, extant, terrestrial

97 vertebrates (Fig. 1a), providing information that has been missing from much of the global

98 conservation planning and prioritization schemes constructed over the last twenty years4. We use

99 our reptile distribution data to: a) examine the congruence in general, hotspot, and endemism

100 richness patterns across all tetrapod classes and among reptile groups; b) explore how current

101 conservation networks and priorities represent reptiles; and c) suggest regions in need of

102 additional conservation attention to target full terrestrial vertebrate representation and highlight

103 current surrogacy gaps, using a formal conservation prioritisation technique.

104 105 Results and Discussion

106 Species richness of reptiles compared to other tetrapods

107 The global pattern of reptile species richness (Fig. 1b) is largely congruent with that of all other

108 terrestrial vertebrates combined (r = 0.824, e.d.f. = 31.2, p << 0.0001; Figs. 2a, S1, Table S1).

109 However, the major reptile groups (Figs. 1c-e, 2b-c, S1, Table S1) show differing degrees of

110 congruence with the other tetrapod taxa. The richness distribution of snakes (Fig. 1d) is very

111 similar to that of other tetrapods (Fig. 2c) in showing pan-tropical dominance (r = 0.873, e.d.f. =

112 30.2, p << 0.0001). Lizard richness is much less similar to non-reptilian tetrapod richness (r =

113 0.501, e.d.f. = 38.3, p << 0.001, Fig. 2b). It is high in both tropical and arid regions, and notably

114 in (Figs. 1c, S1). richness is also less congruent with diversity patterns of the

115 other tetrapods (r = 0.673, e.d.f. = 55.2, p << 0.001), and peaks in the south-eastern USA, the

116 Ganges Delta, and (Fig. 1e).

117 Snakes dominate reptile richness patterns due to their much larger range sizes compared to

118 lizards, even though lizards are about twice as speciose (median ranges size for 3414

119 species: 62,646 km2; for 6415 lizard species: 11,502 km2; Fig. S2). Therefore snakes,

120 disproportionally influence global reptile richness patterns16,17 (Table S1, Fig. S1).

121 Hotspots of richness and range-restricted species

122 As with overall richness patterns, hotspots of richness (the richest 2.5%, 5%, 7.5% and 10% of

123 grid-cells) for all reptiles combined, and of snakes, are largely congruent with those of other

124 tetrapod classes. However they are incongruent with hotspots of lizard or turtle richness (Figs. 3;

125 S3). 126 Congruence in the richness of range-restricted species (those species with the smallest 25% or

127 10% ranges in each group) between tetrapod groups is lower than the congruence across all

128 species1 (Table S1). Endemic lizard and turtle distributions are least congruent with the endemics

129 in other tetrapod classes (Table S1). Global hotspots of relative endemism (or range-size

130 weighted richness, see Methods) for reptiles differ from those of non-reptilian tetrapods (Fig.

131 S4). Island faunas in places such as Socotra, New Caledonia and the Antilles are highlighted for

132 reptiles, while hotspots of endemism for non-reptilian tetrapods are more often continental.

133 The utility of protected areas and current priority schemes in capturing reptile richness

134 Reptiles, like amphibians, are poorly represented in the global network of protected areas (Table

135 S2; Figs. S5, S6). Only 3.5% of reptile and 3.4% of species distributions are

136 contained in protected areas (median species range overlap per , with IUCN categories I-

137 IV), compared with 6.5% for birds and 6% for mammals. Within reptile groups, strict protected

138 areas (IUCN Category I) overlap less with lizard ranges than with other reptile groups but there

139 are no important differences between taxa for the more permissive protected area types (Table

140 S2; Fig. S5). Amphibians have the highest proportion of species whose ranges lie completely

141 outside protected areas, when compared to the other tetrapod groups. Lizards, also fare poorly

142 and have the highest proportion of species outside protected areas when compared to the other

143 reptile groups (Fig. S6a). Turtles have the lowest proportion of species with at least 10% of their

144 range covered by protected areas (Fig. S6b). We suggest that these low overlaps may have been

145 caused by the inability to consider reptile diversity for direct protection, probably arising from

146 ignorance of their distributions.

147 We explored the coverage of all tetrapods in three global prioritisation schemes13,14,18 and a

148 global designation of sites for biodiversity significance15 that have recently used distribution data 149 to highlight regions for targeted conservation. These four global prioritisations/designations

150 cover 6.8%-37.4% of the Earth’s land surface with 34-11,815 unique sites. Terrestrial vertebrate

151 groups have 68%-98% of their species with at least some range covered by these schemes (Fig.

152 S6c). However, reptiles and amphibians are sampled least well by these global schemes, and

153 within reptiles lizards have the lowest representation (Fig. S6c).

154 Fortunately, reptiles seem better situated in terms of conservation costs compared to other

155 tetrapods. The median conservation opportunity cost19 (using the loss of agricultural revenue as a

156 proxy for land-cost) for reptiles is lower than that for other tetrapods (F3, 31850 = 17.4, p < 0.001;

157 Fig. S7). Within reptiles, the opportunity cost is lowest for lizards, and highest for turtles and

158 crocodiles, which could reflect their greater dependence on fresh-water habitats (F3, 10060 = 88.4,

159 p < 0.001; Fig. S7b).

160 Conservation priorities for all tetrapods, incorporating reptile distributions

161 Our results suggest that reptiles, and particularly lizards and turtles, need to be better

162 incorporated into conservation schemes. We used relative endemism within a complementarity

163 analysis20 to identify broad areas within which international and local conservation action should

164 reduce reptile risk (Figs. 4, S8), and repeated this analysis to also incorporate

165 conservation opportunity costs19 (Fig. S8d,e). Many previously identified priority regions13,14,

166 have been retained with the addition of reptile distributions. These include northern and western

167 Australia; central southern USA and the gulf coast of ; the Brazilian Cerrado; Southeast

168 Asia, and many islands.

169 Nevertheless, our analyses also reveal many regions, not currently perceived as biodiversity

170 conservation priorities for tetrapods. These priority areas are predominantly arid and semi-arid 171 habitats (see also Fig. S8f for mean rank change per biome, for prioritisation with and without

172 reptiles). They include parts of northern Africa through the Arabian Peninsula and the Levant;

173 around Lake Chad; in inland arid southern Africa; central Asian arid highlands and steppes;

174 central Australia; the Brazilian Caatinga, and the southern . These regions have been

175 previously neglected as their non-reptile vertebrate biotas were more efficiently represented in

176 other locations. Our analyses show that those locations were poor spatial surrogates for reptile

177 distributions and that conservation efforts in our suggested locations may afford better protection

178 for reptiles while maintaining efficient representation of other vertebrates. We note that many of

179 these locations have low conservation opportunity costs so may be especially attractive for

180 conservation. Furthermore, the location of these areas is not primarily driven by conservation

181 opportunity costs. When these costs are incorporated into the analyses, very similar regions are

182 highlighted for special attention due to the inclusion of reptile distributions (Fig. S8d,e).

183 Summation

184 The complete map of tetrapod species richness presented here reveals important and unique

185 properties of reptile diversity, particularly of lizards and turtles (Figs. 1-3). At a regional scale

186 reptiles have previously been shown to be unusually diverse in arid and semi-arid habitats21-23.

187 Here we reveal that this pattern is global, and further show reptile prominence in island faunas

188 (Figs. 2d, S4). Furthermore, we show that reptiles’ unique diversity patterns have important

189 implications for their conservation. Targeted reptile conservation lags behind that of other

190 tetrapod classes, probably through ignorance24-26. The distributions provided here could make a

191 vital contribution to bridging this gap. Concentrations of in unexpected locations

192 (Fig. 4) require explicit consideration when planning conservation actions. Highlighting such

193 locations for new taxa could be especially beneficial for resource-constrained planning, 194 especially where land costs are low. The lower global congruence with recognized diversity

195 patterns for reptiles should also serve as a warning sign, contrary to some recent suggestions27,

196 for our ability to use distributions of well-studied groups in to predict diversity patterns of

197 poorly known taxa. The distinctive distribution of reptiles, and especially of lizards, suggests that

198 it is driven by different ecological and evolutionary processes to those in other vertebrate

199 taxa23,28. The complete distributions of terrestrial tetrapods we now possess could greatly

200 enhance our ability to study, understand and protect nature.


202 Methods

203 Data collection and assembly was carried out by members of the Global Assessment of Reptile

204 Distributions (GARD) group, which includes all the authors of this paper. Regional specialist

205 group members supervised the integration of geographic data for all species from field guides

206 and books covering the terrestrial reptilian fauna of various regions, as well as revised museum

207 specimen databases, online meta-databases (including the IUCN, GBIF and Vertnet), our own

208 observations and the primary literature. We followed the of the March 2015 edition of

209 the Reptile Database29. Source maps were split or joined on that basis. We used the newest

210 sources available to us. Polygonal maps - representing species extent of occurrence - were

211 preferred over other map types, as such distribution representations are those available for the

212 other classes that were compared to reptiles. Point locality data were modelled to create polygons

213 representing the extent of occurrence using hull geometries (see supplement). Gaps in reptile

214 distribution knowledge for particular locations or taxa were filled using de novo polygon and

215 gridded maps created by GARD members specializing in the fauna of particular regions and

216 taxa. These maps and all data obtained from online databases and the primary literature were 217 then internally vetted, in a manner analogous to the IUCN Specialist Group process. Further

218 details on data collection and curation, modelling of point localities and a full list of data sources

219 per species are available in the supplement. Overall we analysed distribution maps for 10,064

220 extant species, which represent 99% of the species found in the of March 2015.

221 For all analytical purposes we contrasted snakes with the paraphyletic ‘lizards’ (here defined as

222 lepidosaurs exclusive of snakes).

223 Polygonal representations of the extent of species' occurrences, such as we assembled and use in

224 our analyses, are fundamentally important to contemporary conservation planning30. The IUCN's

225 assessment of the extinction risk of individual species requires (and produces) such data, and

226 both they and many other organisations and researchers have used such data in aggregate and at

227 regional-to-global scales for several decades31. Like any representation of species distributions,

228 polygonal range maps can include errors both of omission and commission. Both kinds of

229 inaccuracy can lead to erroneous conclusions by unwary users and this has led to some

230 controversy over the use of polygonal range maps. Of course, all biogeographic representations -

231 specimen localities, SDM outputs, atlas data, polygonal maps and explorers' narratives - lie along

232 this omission: commission spectrum, and can equally be misused or found useless32. For global

233 prioritisation, we follow a comprehensive recent study33 demonstrating the effectiveness of

234 polygonal range maps in highlighting priority areas, despite errors at the level of individual

235 species. We do, however, recognise that specimen data, if collected, curated and made available

236 (at a suitable scale) remains a gold standard for some uses34.

237 Our grid-cell analyses were conducted in a Behrmann Equal Area projection of 48.25 km grid-

238 cells (~0.5° at 30°N/S). All analyses were repeated at a grid size of 96.5 km (~1° at 30°N/S) and 239 results were qualitatively unchanged. GIS and statistical analyses were carried out in R and

240 PostGIS.

241 Range size weighted richness (rswr) was calculated, for each cell, using the following formula:

242 = ∑ where qij is the fraction of the distribution of the species j in the cell i.

243 We used ‘Zonation’20 to produce a ranked prioritisation amongst cells, assuming equal weight to

244 all species and assuming an equal cost for all cells. Cell value was the maximum proportion of

245 any species range represented in it. Cell priority was calculated by iteratively removing the least

246 valuable cell and updating cell values20. We analysed all tetrapod species combined and

247 tetrapods without reptiles separately, to reveal the change in rank importance induced by adding

248 reptile distributions (See supplement, Fig. S8). We repeated our prioritisation using per-cell

249 agricultural opportunity costs19, and found via rank correlation that our priority regions are fairly

250 insensitive to the use of land costs (Figs. 4, S8). 251 Acknowledgments

252 We thank Tamsin Burbidge, Tom Dowe, Shan Huang, Sonia Khela, Hsin-Ying Lee, Karin

253 Tamar, Jonathan Usherwood, Meirion Hopkins and Snir Halle, for help in digitizing reptile

254 ranges. We thank librarians and colleagues for help in obtaining relevant literature, Gill Bunting

255 and Mark Balman for providing IBA polygons and species distribution maps from BirdLife

256 International and Stuart Butchart and four anonymous referees for insightful comments. AB

257 thanks the Gerald M. Lemole endowed Chair funds. GRC thanks CAPES - Coordenação de

258 Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento

259 Científico e Tecnológico – CNPq and Fundação de Apoio à Pesquisa do Distrito Federal –

260 FAPDF for financial support. ID was supported by a Niche Research Grant Scheme,

261 NRGS/1087/2–13(01). CN and MM were supported by São Paulo Research Foundation

262 (FAPESP #2011/50206-9, #2012/19858-2 to CN). MM acknowledges a research fellowship from

263 CNPq. OTC acknowledges support from SENESCYT. RG acknowledges the John Fell Fund of

264 the University of Oxford for support. AA and SM acknowledge support from a BSF grant #

265 2012143.

266 Author contributions

267 AMB, RG, SM, UR conceived the study. RG, CDLO, UR designed the analyses. UR conducted

268 the analyses. AF, SM, MN, UR complied, designed, and curated the dataset. RG, SM, UR wrote

269 the paper. AA, AMB, MB, RB, BC, FCH, LC, GRC, LD, ID, TMD, AF, LLG, MH, YI, FK, AL,


271 PW, YW provided, collated, and verified underlying data. All authors read and commented on

272 the manuscript. 273 UR, AF and MN contributed equally to the paper. RG and SM contributed equally to the paper.

274 Competing interests

275 All authors declare no competing interests.

276 Materials & Correspondence

277 Corresponding author – Shai Meiri, Department of Zoology, Tel-Aviv University, Tel-Aviv

278 6997801, Israel. [email protected]

279 Data availability

280 The reptile distribution data used in this study are available from the corresponding author on

281 reasonable request


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366 Figure 1 – Terrestrial tetrapod species richness maps (0.5º grid-cell resolution). a) all tetrapods

367 including reptiles, b) all reptiles, c) ‘lizards’ d) snakes, e) turtles.

368 Figure 2 – Comparing reptile richness to other tetrapods. Hexagon scatter plots comparing

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377 conservation due to inclusion of reptiles. Cells were ranked in a formal prioritisation scheme20,

378 based on complementarity when ranking cells in an iterative manner. Cells were ranked twice, I-

379 with all tetrapods, II- with all tetrapods excluding reptiles. a) Patterns per 0.5 degree grid-cell

380 where colours represent the priority ranks for the scheme which included all tetrapods (blue =

381 low, red = high). The cells that are highlighted with the bold foreground colours are those that

382 pinpoint those regions that gain in conservation importance due to the inclusion of the reptile

383 data. These cells were selected following these two rules (i) they were in the top 10% of increase

384 in rank, when subtracting the ranks of the analysis with reptiles from the ranks of the analysis

385 without them; and (ii) were part of statistically significant spatial clusters of rank changes (using

386 local Moran’s I35). b) The mean change in rank between prioritizations with and without reptiles 387 (using the above method), per ecoregion (red- ecoregions that become more important due to the

388 inclusion of reptile information; blue – ecoregions becoming less important).